In recent years, with the development of three-dimensional (3D) display technology, processing of stereoscopic images has been increasingly important. In general, the stereoscopic images can be formed in the following ways: for example, using a depth camera that can obtain depth information to photograph, or using dual cameras which can simulate human binocular vision to photograph, and then performing an appropriate image processing for two-dimensional (2D) images to obtain the stereoscopic images.
Stereoscopic image herein means that the objects in the image have different visual depths in addition to the usual two-dimensional images. The technique of converting the 2D images into the stereoscopic images is called stereo matching. Stereo matching means a process of photographing two or more images of a certain scene, estimating a 3D model of the scene by accurately finding matching pixels between the images, and converting 2D positions of the matching pixels into 3D depths.
In the computing technique of conventional stereo matching, one of the two images which are respectively captured by two cameras usually serves as a reference image, and the other serves as a target image. Then, a disparity map of the target image relative to the reference image is output. The disparity of each pixel is inversely proportional to the distance of a photographed object. Therefore, the disparity map can be utilized to depict the 3D depths of the captured image.
However, each of the pixels in the reference image is required to calculate the disparity thereof, and the algorithm of the conventional stereo matching is very complicated, so there is a great amount of computation. Thus, under the restriction of the current semiconductor technology, the stereoscopic photography techniques using a dual camera are still in a developmental stage, it is difficult to reach a commercialization stage.